Abstract Statistical models were developed to estimate the density of Sitophilus zeamais adults in a flat storage warehouse holding 230 tonne of wheat with 12.4 ± 0.2% (wet basis) moisture content at 18–33 °C. Published data were used to develop the models. To valid the developed models, trapping and manual sampling with 15 kg of sampling unit at five locations were conducted in the warehouse for more than 10 wk. Insect densities were calculated by using the developed models and the trapping frequency and temperatures at the sampling locations. The developed models were validated by calculating the average magnitude of relative error (MRE), regression slope, and residues between the calculated and measured insect densities. Three models were developed, and the best model was a linear model. The linear model could explain 96% of the measured insect densities. The temperature on the density prediction has a natural exponential effect.

中文翻译：

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使用探针诱捕器预测小麦仓库中玉米粒蝇成虫密度的统计模型

摘要 开发了统计模型来估计在 18–33 °C 下储存 230 吨小麦、水分含量为 12.4 ± 0.2%（湿基）的扁平储存仓库中玉米粒蝇成虫的密度。已发布的数据用于开发模型。为了验证开发的模型，在仓库中使用 15 kg 采样单元在五个位置进行了捕获和手动采样超过 10 周。通过使用开发的模型以及采样位置的捕获频率和温度来计算昆虫密度。通过计算相对误差 (MRE) 的平均幅度、回归斜率以及计算和测量的昆虫密度之间的残留量来验证开发的模型。开发了三种模型，最好的模型是线性模型。线性模型可以解释 96% 的测量昆虫密度。温度对密度预测具有自然指数效应。